BREAKING NEWS
LATEST POSTS
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OpenCV Python for Computer Vision
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DepthCrafter – Generating Consistent Normals Long Depth Sequences for Open-world Videos
https://depthcrafter.github.io/
We innovate DepthCrafter, a novel video depth estimation approach, by leveraging video diffusion models. It can generate temporally consistent long depth sequences with fine-grained details for open-world videos, without requiring additional information such as camera poses or optical flow.
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ByteDance Loopy: Taming Audio-Driven Portrait Avatar with Long-Term Motion Dependency
https://loopyavatar.github.io/
Loopy supports various visual and audio styles. It can generate vivid motion details from audio alone, such as non-speech movements like sighing, emotion-driven eyebrow and eye movements, and natural head movements.
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Ross Pettit on The Agile Manager – How tech firms went for prioritizing cash flow instead of talent (and artists)
For years, tech firms were fighting a war for talent. Now they are waging war on talent.
This shift has led to a weakening of the social contract between employees and employers, with culture and employee values being sidelined in favor of financial discipline and free cash flow.
The operating environment has changed from a high tolerance for failure (where cheap capital and willing spenders accepted slipped dates and feature lag) to a very low – if not zero – tolerance for failure (fiscal discipline is in vogue again).
While preventing and containing mistakes staves off shocks to the income statement, it doesn’t fundamentally reduce costs. Years of payroll bloat – aggressive hiring, aggressive comp packages to attract and retain people – make labor the biggest cost in tech.
…Of course, companies can reduce their labor force through natural attrition. Other labor policy changes – return to office mandates, contraction of fringe benefits, reduction of job promotions, suspension of bonuses and comp freezes – encourage more people to exit voluntarily. It’s cheaper to let somebody self-select out than it is to lay them off.
…Employees recruited in more recent years from outside the ranks of tech were given the expectation that we’ll teach you what you need to know, we want you to join because we value what you bring to the table. That is no longer applicable. Runway for individual growth is very short in zero-tolerance-for-failure operating conditions. Job preservation, at least in the short term for this cohort, comes from completing corporate training and acquiring professional certifications. Training through community or experience is not in the cards.
…The ability to perform competently in multiple roles, the extra-curriculars, the self-directed enrichment, the ex-company leadership – all these things make no matter. The calculus is what you got paid versus how you performed on objective criteria relative to your cohort. Nothing more.
…Here is where the change in the social contract is perhaps the most blatant. In the “destination employer” years, the employee invested in the community and its values, and the employer rewarded the loyalty of its employees through things like runway for growth (stretch roles and sponsored work innovation) and tolerance for error (valuing demonstrable learning over perfection in execution). No longer.
…http://www.rosspettit.com/2024/08/for-years-tech-was-fighting-war-for.html
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2DGS – 2D Gaussian Splatting for Geometrically Accurate Radiance Fields
A 2D Gaussian Splats technique for extracting cleaner 3D geometry from 3DGS
https://github.com/hbb1/2d-gaussian-splatting
https://surfsplatting.github.io/
https://colab.research.google.com/drive/1qoclD7HJ3-o0O1R8cvV3PxLhoDCMsH8W
3D Gaussian Splatting (3DGS) has recently revolutionized radiance field reconstruction, achieving high quality novel view synthesis and fast rendering speed without baking. However, 3DGS fails to accurately represent surfaces due to the multi-view inconsistent nature of 3D Gaussians. We present 2D Gaussian Splatting (2DGS), a novel approach to model and reconstruct geometrically accurate radiance fields from multi-view images. Our key idea is to collapse the 3D volume into a set of 2D oriented planar Gaussian disks. Unlike 3D Gaussians, 2D Gaussians provide view-consistent geometry while modeling surfaces intrinsically. To accurately recover thin surfaces and achieve stable optimization, we introduce a perspective-accurate 2D splatting process utilizing ray-splat intersection and rasterization. Additionally, we incorporate depth distortion and normal consistency terms to further enhance the quality of the reconstructions. We demonstrate that our differentiable renderer allows for noise-free and detailed geometry reconstruction while maintaining competitive appearance quality, fast training speed, and real-time rendering.
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Kiosk – Library Tool for 3D Artists
Kiosk streamlines resource management. With tailored filtering, customizable organization, and seamless integration into Maya, Houdini, Blender and Cinema4D. Maintain one library for them all!
https://fabianstrube.gumroad.com/l/kiosk-library
FEATURED POSTS
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David Cahn – AI’s $600B Question, is it a sustainable bubble?
https://www.sequoiacap.com/article/ais-600b-question
The expanding economic impact of AI, highlights a significant gap between AI infrastructure investments and actual revenue generation. Despite easing GPU shortages and increased investments by cloud providers, AI-related revenue, particularly dominated by OpenAI, remains insufficient to justify the massive capital expenditures. The analysis reveals that this gap has grown from $125 billion to $500 billion, posing challenges for the AI industry while emphasizing the need for realistic expectations and sustainable value creation.
OpenAI training and inference costs could reach $7bn for 2024, AI startup set to lose $5bn – report
AI: Are we in another dot-com bubble?
The power of AI will transform every facet of our society, from the micro changes in our day-to-day lives to the macro changes in global geopolitics. It will challenge our values and assumptions and make us reconsider what it means to be human. It is inevitable that some capital will be wasted getting there. We may even experience a bubble or two. But this is part of the growing pains of advancing humankind. Society, like our individual lives, seldom take the shortest route. As to the argument that we are in a bubble right now, we think it deserves some reconsidering.
https://kelvinmu.substack.com/p/ai-are-we-in-another-dot-com-bubble
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AI Data Laundering: How Academic and Nonprofit Researchers Shield Tech Companies from Accountability
“Simon Willison created a Datasette browser to explore WebVid-10M, one of the two datasets used to train the video generation model, and quickly learned that all 10.7 million video clips were scraped from Shutterstock, watermarks and all.”
“In addition to the Shutterstock clips, Meta also used 10 million video clips from this 100M video dataset from Microsoft Research Asia. It’s not mentioned on their GitHub, but if you dig into the paper, you learn that every clip came from over 3 million YouTube videos.”
“It’s become standard practice for technology companies working with AI to commercially use datasets and models collected and trained by non-commercial research entities like universities or non-profits.”
“Like with the artists, photographers, and other creators found in the 2.3 billion images that trained Stable Diffusion, I can’t help but wonder how the creators of those 3 million YouTube videos feel about Meta using their work to train their new model.”
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Virtual Production volumes study
Color Fidelity in LED Volumes
https://theasc.com/articles/color-fidelity-in-led-volumes
Virtual Production Glossary
https://vpglossary.com/What is Virtual Production – In depth analysis
https://www.leadingledtech.com/what-is-a-led-virtual-production-studio-in-depth-technical-analysis/
A comparison of LED panels for use in Virtual Production:
Findings and recommendations
https://eprints.bournemouth.ac.uk/36826/1/LED_Comparison_White_Paper%281%29.pdf
